Detecting relative crowd density via client devices

ABSTRACT

Detecting crowds is provided. A location is selected in a set of locations a user of a client device wants to go to based on data within a profile associated with the user. A set of data inputs is monitored to determine a number of people currently at the selected location. Then, in response to determining that the number of people currently at the selected location is not greater than a user-defined threshold level of people for the selected location, a mapped route to the selected location is sent to the client device of the user.

BACKGROUND

1. Field

The disclosure relates generally to crowd detection and morespecifically to managing movements of a client device user based on aplurality of different data inputs.

2. Description of the Related Art

In today's busy world, people want to be able to conduct their dailyshopping, such as grocery shopping, quickly and easily. Similarly,stores want to provide their customers with a pleasant shoppingexperience, which includes increasing the speed at which the customerscan complete their shopping. However, many shoppers dislike dealing withcrowded stores. For example, it may be an inconvenience for a shopper tomaneuver around other shoppers in a crowded store and a crowded storemay represent longer lines during the shopping experience. At a crowdedgrocery store this may mean longer lines at, for example, the bakery,meat counter, deli, and check out station, which increases a shopper'stime spent at the grocery store and decreases the shopper's overallexperience.

SUMMARY

According to one illustrative embodiment, a method for detecting crowdsis provided. A computer selects a location in a set of locations a userof a client device wants to go to based on data within a profileassociated with the user. The computer monitors a set of data inputs todetermine a number of people currently at the selected location. Then,in response to the computer determining that the number of peoplecurrently at the selected location is not greater than a user-definedthreshold level of people for the selected location, the computer sendsa mapped route to the selected location to the client device of theuser. According to other illustrative embodiments, a computer system anda computer program product for detecting crowds are provided.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

FIG. 1 is a pictorial representation of a network of data processingsystems in which illustrative embodiments may be implemented;

FIG. 2 is a diagram of a data processing system in which illustrativeembodiments may be implemented;

FIG. 3 is a diagram illustrating an example of a crowd detection systemin accordance with an illustrative embodiment;

FIG. 4 is a diagram illustrating an example of a plurality of differentdata inputs in accordance with an illustrative embodiment;

FIG. 5 is a diagram illustrating an example of a location in accordancewith an illustrative embodiment;

FIG. 6A and FIG. 6B are a flowchart illustrating a process for detectinga crowd at a location in accordance with an illustrative embodiment;

FIG. 7A and FIG. 7B are a flowchart illustrating a process for detectinga crowd at a site corresponding to a task at a location in accordancewith an illustrative embodiment; and

FIG. 8A and FIG. 8B are a flowchart illustrating a process for a clientdevice in accordance with an illustrative embodiment.

DETAILED DESCRIPTION

As will be appreciated by one skilled in the art, aspects of theillustrative embodiments may be embodied as a computer system, computerimplemented method, or computer program product. Accordingly, aspects ofthe illustrative embodiments may take the form of an entirely hardwareembodiment, an entirely software embodiment (including firmware,resident software, micro-code, etc.), or an embodiment combiningsoftware and hardware aspects that may all generally be referred toherein as a “circuit,” “module,” or “system.” Furthermore, aspects ofthe illustrative embodiments may take the form of a computer programproduct embodied in one or more computer readable medium(s) havingcomputer readable program code embodied thereon.

Any combination of one or more computer readable medium(s) may beutilized. The computer readable medium may be a computer readable signalmedium or a computer readable storage medium. A computer readablestorage medium may be, for example, but not limited to, an electronic,magnetic, optical, electromagnetic, infrared, or semiconductor system,apparatus, or device, or any suitable combination of the foregoing. Morespecific examples (a non-exhaustive list) of the computer readablestorage medium would include the following: an electrical connectionhaving one or more wires, a portable computer diskette, a hard disk, arandom access memory (RAM), a read-only memory (ROM), an erasableprogrammable read-only memory (EPROM or Flash memory), an optical fiber,a portable compact disc read-only memory (CD-ROM), an optical storagedevice, a magnetic storage device, or any suitable combination of theforegoing. In the context of this document, a computer readable storagemedium may be any tangible medium that can contain or store a programfor use by or in connection with an instruction execution system,apparatus, or device.

A computer readable signal medium may include a propagated data signalwith computer readable program code embodied therein, for example, inbaseband or as part of a carrier wave. Such a propagated signal may takeany of a variety of forms, including, but not limited to,electro-magnetic, optical, or any suitable combination thereof. Acomputer readable signal medium may be any computer readable medium thatis not a computer readable storage medium and that can communicate,propagate, or transport a program for use by or in connection with aninstruction execution system, apparatus, or device.

Program code embodied on a computer readable medium may be transmittedusing any appropriate medium, including but not limited to wireless,wireline, optical fiber cable, RF, etc., or any suitable combination ofthe foregoing.

Computer program code for carrying out operations for aspects of theillustrative embodiments may be written in any combination of one ormore programming languages, including an object oriented programminglanguage such as Java, Smalltalk, C++ or the like and conventionalprocedural programming languages, such as the “C” programming languageor similar programming languages. The program code may execute entirelyon the user's computer, partly on the user's computer, as a stand-alonesoftware package, partly on the user's computer and partly on a remotecomputer or entirely on the remote computer or server. In the latterscenario, the remote computer may be connected to the user's computerthrough any type of network, including a local area network (LAN) or awide area network (WAN), or the connection may be made to an externalcomputer (for example, through the Internet using an Internet ServiceProvider).

Aspects of the illustrative embodiments are described below withreference to flowchart illustrations and/or block diagrams of methods,apparatus (systems), and computer program products according toembodiments of the invention. It will be understood that each block ofthe flowchart illustrations and/or block diagrams, and combinations ofblocks in the flowchart illustrations and/or block diagrams, can beimplemented by computer program instructions. These computer programinstructions may be provided to a processor of a general purposecomputer, special purpose computer, or other programmable dataprocessing apparatus to produce a machine, such that the instructions,which execute via the processor of the computer or other programmabledata processing apparatus, create means for implementing thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

These computer program instructions may also be stored in a computerreadable medium that can direct a computer, other programmable dataprocessing apparatus, or other devices to function in a particularmanner, such that the instructions stored in the computer readablemedium produce an article of manufacture including instructions whichimplement the function/act specified in the flowchart and/or blockdiagram block or blocks.

The computer program instructions may also be loaded onto a computer,other programmable data processing apparatus, or other devices to causea series of operational steps to be performed on the computer, otherprogrammable apparatus or other devices to produce a computerimplemented process such that the instructions which execute on thecomputer or other programmable apparatus provide processes forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks.

With reference now to the figures, and in particular, with reference toFIGS. 1-3, diagrams of data processing environments are provided inwhich illustrative embodiments may be implemented. It should beappreciated that FIGS. 1-3 are only meant as examples and are notintended to assert or imply any limitation with regard to theenvironments in which different embodiments may be implemented. Manymodifications to the depicted environments may be made.

FIG. 1 depicts a pictorial representation of a network of dataprocessing systems in which illustrative embodiments may be implemented.Network data processing system 100 is a network of computers and otherdevices in which the illustrative embodiments may be implemented.Network data processing system 100 contains network 102, which is themedium used to provide communications links between the computers andthe other various devices connected together within network dataprocessing system 100. Network 102 may include connections, such aswire, wireless communication links, or fiber optic cables.

In the depicted example, server 104 and server 106 connect to network102, along with storage unit 108. Server 104 and server 106 may be, forexample, server computers with high speed connections to network 102. Inaddition, server 104 and/or server 106 may provide services fordetecting crowds of people at different locations and managing movementsof users of client devices connected to network 102 based on a pluralityof different data inputs corresponding to those locations.

Clients 110, 112, and 114 also connect to network 102. Clients 110, 112,and 114 are clients to server 104 and/or server 106. In the depictedexample, server 104 and/or server 106 may provide information, such asboot files, operating system images, and applications to clients 110,112, and 114.

Clients 110 and 112 may be, for example, mobile data processing systems,such as cellular telephones, smart phones, personal digital assistants,gaming devices, or handheld computers, with wireless communication linksto network 102. Also, clients 110 and 112 may include a tracking unit,such as tracking units 116 and 118. Client 114 may be, for example, apersonal computer, a network computer, or a portable computer, such as alaptop computer.

Tracking units 116 and 118 may include, for example, global positioningsystem (GPS) transceivers and/or radio frequency identification (RFID)tags. Tracking units 116 and 118 provide current location datacorresponding to clients 110 and 112. Clients 110 and 112 may send thelocation data corresponding to the current location of clients 110 and112 to server 104 and/or server 106 on a continuous basis, on apredetermined time interval basis, or on demand.

Moreover, clients 110, 112, and 114 may send other data, such as, forexample, user profile data associated with users of clients 110, 112,and 114 to server 104 and/or server 106. The user profile data mayinclude, for example, preferences, electronic calendar entries,electronic task lists, user-defined crowd threshold levels, and historydata corresponding to the users. Of course, the user profile data mayinclude any information associated with a user of a client device.Server 104 and/or server 106 may utilize the user profile data to routeusers of the client devices to locations the users want to go to and tosites within those locations to perform different tasks.

Storage unit 108 is a network storage device capable of storing data ina structured or unstructured format. Storage unit 108 may provide, forexample, storage of names and identification numbers of a plurality ofusers, user profiles corresponding to the plurality of users, userhistory data, video data corresponding to user activities at differentlocations, and network addresses, such as uniform resource locators(URLs), of social media web sites associated with each user in theplurality of users. Furthermore, storage unit 108 may store other data,such as security information that may include user names, passwords,and/or biometric data associated with system administrators and otherusers of the crowd detection and routing service.

Moreover, it should be noted that network data processing system 100 mayinclude any number of additional server devices, client devices, andother devices not shown. Program code located in network data processingsystem 100 may be stored on a computer recordable storage medium anddownloaded to a computer or other device for use. For example, programcode may be stored on a computer recordable storage medium on server 104and downloaded to client 110 over network 102 for use on client 110.

In the depicted example, network data processing system 100 is theInternet with network 102 representing a worldwide collection ofnetworks and gateways that use the Transmission ControlProtocol/Internet Protocol (TCP/IP) suite of protocols to communicatewith one another. At the heart of the Internet is a backbone ofhigh-speed data communication lines between major nodes or hostcomputers, consisting of thousands of commercial, governmental,educational, and other computer systems that route data and messages. Ofcourse, network data processing system 100 also may be implemented as anumber of different types of networks, such as for example, an intranet,a local area network (LAN), or a wide area network (WAN). FIG. 1 isintended as an example, and not as an architectural limitation for thedifferent illustrative embodiments.

With reference now to FIG. 2, a diagram of a data processing system isdepicted in accordance with an illustrative embodiment. Data processingsystem 200 is an example of a computer or other type of data processingsystem, such as server 104 or client 110 in FIG. 1, in which computerreadable program code or instructions implementing processes ofillustrative embodiments may be located. In this illustrative example,data processing system 200 includes communications fabric 202, whichprovides communications between processor unit 204, memory 206,persistent storage 208, communications unit 210, input/output (I/O) unit212, and display 214.

Processor unit 204 serves to execute instructions for softwareapplications or programs that may be loaded into memory 206. Processorunit 204 may be a set of one or more processors or may be amulti-processor core, depending on the particular implementation.Further, processor unit 204 may be implemented using one or moreheterogeneous processor systems, in which a main processor is presentwith secondary processors on a single chip. As another illustrativeexample, processor unit 204 may be a symmetric multi-processor systemcontaining multiple processors of the same type.

Memory 206 and persistent storage 208 are examples of storage devices216. A computer readable storage device is any piece of hardware that iscapable of storing information, such as, for example, withoutlimitation, data, computer readable program code in functional form,and/or other suitable information either on a transient basis and/or apersistent basis. Further, a computer readable storage device does notinclude a non-statutory propagation medium. Memory 206, in theseexamples, may be, for example, a random access memory, or any othersuitable volatile or non-volatile storage device. Persistent storage 208may take various forms, depending on the particular implementation. Forexample, persistent storage 208 may contain one or more devices. Forexample, persistent storage 208 may be a hard drive, a flash memory, arewritable optical disk, a rewritable magnetic tape, or some combinationof the above. The media used by persistent storage 208 may be removable.For example, a removable hard drive may be used for persistent storage208.

Communications unit 210, in this example, provides for communicationwith other data processing systems or devices. Communications unit 210may provide communications through the use of either or both physicaland wireless communications links. The physical communications link mayutilize, for example, a wire, cable, universal serial bus, or any otherphysical technology to establish a physical communications link for dataprocessing system 200. The wireless communications link may utilize, forexample, shortwave, high frequency, ultra high frequency, microwave,wireless fidelity (Wi-Fi), bluetooth technology, global system formobile communications (GSM), code division multiple access (CDMA),second-generation (2G), third-generation (3G), fourth-generation (4G),or any other wireless communication technology or standard to establisha wireless communications link for data processing system 200.

Input/output unit 212 allows for the input and output of data with otherdevices that may be connected to data processing system 200. Forexample, input/output unit 212 may provide a connection for user inputthrough a keypad, a keyboard, a mouse, and/or some other suitable inputdevice. Display 214 provides a mechanism to display information to auser. In addition, display 214 may include touch screen capabilities toreceive inputs from a user.

Instructions for the operating system, applications, and/or programs maybe located in storage devices 216, which are in communication withprocessor unit 204 through communications fabric 202. In thisillustrative example, the instructions are in a functional form onpersistent storage 208. These instructions may be loaded into memory 206for running by processor unit 204. The processes of the differentembodiments may be performed by processor unit 204 using computerimplemented instructions, which may be located in a memory, such asmemory 206. These instructions are referred to as program code, computerusable program code, or computer readable program code that may be readand run by a processor in processor unit 204. The program code, in thedifferent embodiments, may be embodied on different physical computerreadable storage devices, such as memory 206 or persistent storage 208.

Program code 218 is located in a functional form on computer readablemedia 220 that is selectively removable and may be loaded onto ortransferred to data processing system 200 for running by processor unit204. Program code 218 and computer readable media 220 form computerprogram product 222. In one example, computer readable media 220 may becomputer readable storage media 224 or computer readable signal media226. Computer readable storage media 224 may include, for example, anoptical or magnetic disc that is inserted or placed into a drive orother device that is part of persistent storage 208 for transfer onto astorage device, such as a hard drive, that is part of persistent storage208. Computer readable storage media 224 also may take the form of apersistent storage, such as a hard drive, a thumb drive, or a flashmemory that is connected to data processing system 200. In someinstances, computer readable storage media 224 may not be removable fromdata processing system 200.

Alternatively, program code 218 may be transferred to data processingsystem 200 using computer readable signal media 226. Computer readablesignal media 226 may be, for example, a propagated data signalcontaining program code 218. For example, computer readable signal media226 may be an electro-magnetic signal, an optical signal, and/or anyother suitable type of signal. These signals may be transmitted overcommunication links, such as wireless communication links, an opticalfiber cable, a coaxial cable, a wire, and/or any other suitable type ofcommunications link. In other words, the communications link and/or theconnection may be physical or wireless in the illustrative examples. Thecomputer readable media also may take the form of non-tangible media,such as communication links or wireless transmissions containing theprogram code.

In some illustrative embodiments, program code 218 may be downloadedover a network to persistent storage 208 from another device or dataprocessing system through computer readable signal media 226 for usewithin data processing system 200. For instance, program code stored ina computer readable storage media in a server data processing system maybe downloaded over a network from the server to data processing system200. The data processing system providing program code 218 may be aserver computer, a client computer, or some other device capable ofstoring and transmitting program code 218.

The different components illustrated for data processing system 200 arenot meant to provide architectural limitations to the manner in whichdifferent embodiments may be implemented. The different illustrativeembodiments may be implemented in a data processing system includingcomponents in addition to, or in place of, those illustrated for dataprocessing system 200. Other components shown in FIG. 2 can be variedfrom the illustrative examples shown. The different embodiments may beimplemented using any hardware device or system capable of executingprogram code. As one example, data processing system 200 may includeorganic components integrated with inorganic components and/or may becomprised entirely of organic components excluding a human being. Forexample, a storage device may be comprised of an organic semiconductor.

As another example, a computer readable storage device in dataprocessing system 200 is any hardware apparatus that may store data.Memory 206, persistent storage 208, and computer readable storage media224 are examples of physical storage devices in a tangible form.

In another example, a bus system may be used to implement communicationsfabric 202 and may be comprised of one or more buses, such as a systembus or an input/output bus. Of course, the bus system may be implementedusing any suitable type of architecture that provides for a transfer ofdata between different components or devices attached to the bus system.Additionally, a communications unit may include one or more devices usedto transmit and receive data, such as a modem or a network adapter.Further, a memory may be, for example, memory 206 or a cache such asfound in an interface and memory controller hub that may be present incommunications fabric 202.

In the course of developing illustrative embodiments, it was discoveredthat people dealing with the problem of crowded stores will drive by astore to identify how many cars are in the parking lot. Or, people willjust avoid certain days of the week or avoid certain hours of the daywhen they know there will be crowds of shoppers. However, this may be aninconvenience to these people and may not be based on currentinformation.

Thus, illustrative embodiments provide users with real time dataregarding how crowded a store is currently or how crowded a store may beat a future time based on historical data. Illustrative embodiments mayutilize video surveillance, presence detection, and crowd densityestimation to determine the number of people that are congregated in anygiven area. A user may utilize this crowd detection information todetermine whether to make a trip to a particular store or to determinewhich particular aisle to go to in a store to help optimize theshopper's time.

Consequently, illustrative embodiments allow users to avoid crowdedlocations, optimize their time, and have a more pleasant experience as aresult of having less stress due to decreased crowd exposure. Further,by users avoiding crowded stores, retail establishments may receive abenefit from having a more even flow of shoppers. An even flow ofshoppers may enable a retail establishment to operate more efficiently,avoid stock outs, and provide a more relaxed environment for theirshoppers.

Illustrative embodiments take into account shopping list or task listdata of users, as well as other data, such as crowd density estimationat a location, presence detection, preferences corresponding to aparticular user and other shoppers at a location, and real time locationdata corresponding to the user and the other shoppers at the location.Furthermore, illustrative embodiments take into account informationobtained from a number of other sources, such as, for example, videosurveillance cameras, motion detectors, radio frequency identificationreaders, and social media web sites.

Illustrative embodiments utilize all of this gathered information on acontinuous basis to calculate, for example, the most efficient route tonavigate to and through a store or other location. It should be notedthat illustrative embodiments may continuously update a route to helpensure that illustrative embodiments provide a user with the best routepossible based on user preferences and crowd detection. User preferencesmay include, for example, the fastest route through a store, mostrelaxed environment, routing to new products, routing to free samples,et cetera.

Illustrative embodiments also may calculate the best time to go to astore on a given day or week based on the user preferences and real timedata. In addition, illustrative embodiments may calculate how manycheckout personnel are needed to satisfy current and future demand basedon real time data of shoppers moving through a store. For example, byillustrative embodiments knowing the routes of different shoppersthrough a store, illustrative embodiments may calculate when thesedifferent shoppers may arrive at checkout stations. Further,illustrative embodiments may route different shoppers to differentcheckout stations with minimum queue sizes to ensure a better checkoutexperience. Hence, retail establishments also may benefit fromillustrative embodiments providing this service to their customers.

Thus, illustrative embodiments provide a method, computer system, andcomputer program product for detecting crowds. A computer selects alocation in a set of locations a user of a client device wants to go tobased on data, such as an electronic task list, within a profileassociated with the user. The computer monitors a set of data inputs todetermine a number of people currently at the selected location. Then,in response to the computer determining that the number of peoplecurrently at the selected location is not greater than a user-definedthreshold level of people for the selected location, the computer sendsa mapped route to the selected location to the client device of theuser. The mapped route may be based on, for example, a selected taskwithin the electronic task list and an estimated time to navigate to theselected task and an estimated time to complete the selected task.Moreover, the mapped route may be based on an estimated crowd densityand a determined impact the estimated crowd density has on the mappedroute.

With reference now to FIG. 3, a diagram illustrating an example of acrowd detection system is depicted in accordance with an illustrativeembodiment. Crowd detection system 300 may be implemented in, forexample, a network of data processing systems, such as network dataprocessing system 100 in FIG. 1. Crowd detection system 300 includesserver device 302, client device 304, user profile database 306,tracking system component 308, mapping system component 310, videosystem component 312, presence detection component 314, and crowddensity estimation component 316. However, it should be noted crowddetection system 300 is only intended as an example and not intended asa limitation on illustrative embodiments. For example, crowd detectionsystem 300 may include more or fewer devices and components than shown.

Server device 302 and client device 304 may be, for example, server 104and client 110 in FIG. 1. Server device 302 includes route and spacemanagement application 318. Route and space management application 318is a software program that is capable of determining the number ofpeople at a location and managing movements of client device users atthat location based on a plurality of different data inputs from aplurality of different sources, such as user profile database 306,tracking system component 308, mapping system component 310, videosystem component 312, presence detection component 314, and crowddensity estimation component 316.

User profile database 306 stores a plurality of user profiles, such asuser profile 320, which corresponds to a plurality of different users ofcrowd detection system 300. User profile 320 is the profile of the userassociated with client device 304 and includes user preferences 322,electronic calendar entries 324, electronic task lists 326, user-definedcrowd threshold levels 328, and history data 330. However, it should benoted that user profile 320 may include any information corresponding tothe user of client device 304.

User preferences 322 include preferences of the user of client device304, such as preferred order of locations the user wants to go to,preferred travel routes to the locations, preferred travel routes withinthe locations, preferred products to obtain at the locations, et cetera.Electronic calendar entries 324 are entries in an electronic calendarassociated with the user of client device 304 and may containinformation, such as times and locations of events the user wants to goto. Electronic task lists 326 are a set of one or more lists of tasksthe user of client device 304 wants to perform at a set of one or morelocations. Electronic task lists 326 may include, for example, a set ofone or more shopping lists of products the user of client device 304wants to purchase at a set of one or more known locations. In addition,electronic task lists 326 may include, for example, a set of one or moreactivities the user of client device 304 wants to do at an amusementpark.

User-defined crowd threshold levels 328 are threshold numbers of peopledefined by the user of client device 304. Route and space managementapplication 318 may utilize user-defined crowd threshold levels 328 todetermine whether to route the user of client device 304 to a particularlocation or to a particular site within that location if the currentnumber of people is greater than the user-defined threshold level forthat location or site within that location. However, if user-definedcrowd threshold levels 328 are not available, route and space managementapplication 318 may utilize default crowd threshold levels. History data330 is information associated with the user of client device 304, suchas past purchase history of the user, previous routes to and through alocation taken by the user, video recordings of the user in thelocation, et cetera. In addition, history data 330 may include a recordof locations, along with dates and times, where the user traveled to tocomplete tasks within electronic task lists 326. Further, history data330 may include determined behavior patterns of the user at thelocations and determined behavior patterns of other people at thoselocations.

Route and space management application 318 may utilize tracking systemcomponent 308 to track a current position of client device 304. Trackingsystem component 308 includes a plurality of hardware and softwarecomponents necessary to track client device 304. Tracking systemcomponent 308 may include, for example, global positioning systemtechnology, radio frequency identification technology, or any othertechnology capable of tracking the current position of client device304.

Route and space management application 318 may utilize mapping systemcomponent 310 to map routes to and through different locations for theuser of client device 304 to follow. Mapping system component 310 mayinclude, for example, city maps, maps of store layouts, and any othertype of maps needed to route the user of client device 304. Route andspace management application 318 may utilize video system component 312to detect the user of client device 304 using, for example, facialrecognition technology. Also, route and space management application 318may utilize video system component 312 to detect the presence and thenumber of other people at a location. Video system component 312 is anetwork of video surveillance cameras at the location. In addition,route and space management application 318 may utilize video systemcomponent 312 to determine historical congestion points and patterns ata location and then monitor those congestion points at an increasedfrequency. Further, route and space management application 318 maymonitor crowd densities at those congestion points on a predeterminedtime interval basis, such as, for example, every minute, and reroute theuser of client device 304 based on the monitored crowd densities atthose congestion points.

Route and space management application 318 may utilize presencedetection component 314 to detect the presence of people at a location.Presence detection component 314 may include, for example, motion sensortechnology. Route and space management application 318 may utilize crowddensity estimation component 316 to estimate the number of peoplecurrently at a location or estimate the number of people that may be atthe location at a future time. Crowd density estimation component 316may utilize data obtained by tracking system component 308, video systemcomponent 312, and presence detection component 314 to estimate acurrent crowd density at a location and/or a future crowd density basedon determined historical crowd density patterns.

With reference now to FIG. 4, a diagram illustrating an example of aplurality of different data inputs is depicted in accordance with anillustrative embodiment. A crowd detection system, such as crowddetection system 300 in FIG. 3, may utilize data inputs 400 to determinethe number of people at a location and manage movements of client deviceusers at that location. Data inputs 400 include video camera data 402,motion sensor data 404, radio frequency identification reader data 406,navigation data 408, social media web site data 410, electronic tasklist data 412, user profile data 414, and store map and inventory data416.

Video camera data 402 are video images of one or more people at alocation and may be obtained by, for example, a video system component,such as video system component 312 in FIG. 3. Motion sensor data 404 aredata corresponding to a presence of one or more people at a location andmay be obtained by, for example, a presence detection component, such aspresence detection component 314 in FIG. 3. Radio frequencyidentification reader data 406 are data corresponding to radio frequencyidentification tags associated with client devices and/or storemerchandize and may be obtained by, for example, a tracking systemcomponent, such as tracking system component 308 in FIG. 3.

Navigation data 408 are data corresponding to routes to and through alocation and may be obtained by, for example, a mapping systemcomponent, such as mapping system component 310 in FIG. 3. Social mediaweb site data 410 are information posted by users and other peopleidentifying locations and future locations of the users and otherpeople. Social media web site data 410 may be obtained by, for example,a crowd density estimation component, such as crowd density estimationcomponent 316 in FIG. 3.

Electronic task list data 412 are data in a set of one or moreelectronic task lists, such as electronic task lists 326 in FIG. 3. Userprofile data 414 are data in a user profile, such as user profile 320 inFIG. 3. Store map and inventory data 416 are data related to a layout ofa store or other location and may include merchandize inventoryinformation of the store. Store map and inventory data 416 may beobtained from the mapping system component, for example.

With reference now to FIG. 5, a diagram illustrating an example of alocation is depicted in accordance with an illustrative embodiment.Location 500 may be, for example, a store, an amusement park, abuilding, et cetera. Location 500 includes presence detection component502, video system component 504, and crowd density estimation component506, such as presence detection component 314, video system component312, and crowd density estimation component 316 in FIG. 3.

Presence detection component 502 detects the presence of client deviceuser 518 entering location 500 at entrance 514. Presence detectioncomponent 502 sends this information to a server in a crowd detectionsystem, such as server device 302 in crowd detection system 300 in FIG.3. The crowd detection system server utilizes data inputs from videosystem component 504 and crowd density estimation component 506 todetermine the location and number of people in location 500. Using thedata obtained from video system component 504 and crowd densityestimation component 506, the crowd detection system server routesclient device user 518 to site corresponding to task 510 via route 520.Site corresponding to task 510 may be, for example, the site of a taskin a list of tasks client device user 518 wants to perform at location500. The task may be, for example, picking out a box of cereal at 510.The crowd detection system server routes client device user 518 based onthe tasks within an electronic tasks list, locations and sitescorresponding to the tasks within the electronic tasks list, andestimated current crowd densities at those locations and sites.Moreover, the crowd detection system server may estimate future crowddensities at currently crowded locations and sites corresponding to thetasks within the electronic tasks list based on determined historicalcrowd density patterns and reroute client device user 518 accordingly.

When client device user 518 leaves site corresponding to task 510, thecrowd detection system server routes client device user 518 to sitecorresponding to task 508 via route 526. The task at 508 may be, forexample, picking out a carton of eggs. The crowd detection system serverdoes not utilize route 522 because of detected number of people aboveuser-defined threshold 524. Detected number of people above user-definedthreshold 524 may be, for example, a user-defined crowd threshold levelin user-defined crowd threshold levels 328 in FIG. 3 or may be a defaultcrowd threshold level.

When client device user 518 leaves site corresponding to task 508, thecrowd detection system server routes client device user 518 to sitecorresponding to task 512 via route 528. The task at 512 may be, forexample, checking out. The crowd detection system server may routeclient device user 518 to a check out station with the fewest number ofpeople standing in line at 512. Afterward, the crowd detection systemserver routes client device user 518 to exit 516 via route 530.

With reference now to FIG. 6A and FIG. 6B, a flowchart illustrating aprocess for detecting a crowd at a location is shown in accordance withan illustrative embodiment. The process shown in FIGS. 6A and 6B may beimplemented in a server device, such as, for example, server device 302in FIG. 3. In addition, the server device may be implemented in a dataprocessing system, such as data processing system 200 in FIG. 2.

The process begins when the server device receives a profile associatedwith a user of a client device, such as user profile 320 in FIG. 3 (step602). The client device may be, for example, client device 304 in FIG.3. The server device may store the user profile in a user profiledatabase, such as user profile database 306 in FIG. 3.

After receiving the profile in step 602, the server device determines aset of one or more locations the user of the client device wants to goto based on data within the profile associated with the user (step 604).The set of one or more locations the user of the client device wants togo to may be, for example, location 500 in FIG. 5. The data in the userprofile that the server device uses to determine the set of location maybe, for example, preferences, electronic calendar entries, electronictask lists, and/or history data associated with the user, such as datain user preferences 322, electronic calendar entries 324, electronictask lists 326, and history data 330 in FIG. 3.

In addition, the server device selects a location in the set oflocations the user of the client device wants to go to based on the datawithin the profile associated with the user (step 606). Subsequent toselecting the location in step 606, the server device monitors a set ofone or more data inputs to determine a number of people currently at theselected location (step 608). The set of data inputs may be, forexample, data inputs 400 in FIG. 4.

Further, the server device makes a determination as to whether thenumber of people currently at the selected location is greater than auser-defined threshold level of people for the location (step 610). Theuser-defined threshold level of people for the location may be, forexample, a user-defined crowd threshold level in user-defined crowdthreshold levels 328 in FIG. 3. If the server device determines that thenumber of people currently at the selected location is greater than theuser-defined threshold level of people for the location, yes output ofstep 610, then the process proceeds to step 626. If the server devicedetermines that the number of people currently at the selected locationis not greater than the user-defined threshold level of people for thelocation, no output of step 610, then the server device maps a route tothe location using a mapping system component (step 612). The mappingsystem component may be, for example, mapping system component 310 inFIG. 3.

Furthermore, the server device sends the mapped route to the location tothe client device of the user (step 614). The server device alsomonitors a current location of the client device of the user using atracking system component (step 616). The tracking system component maybe, for example, tracking system component 308 in FIG. 3.

Moreover, the server device makes a determination as to whether theclient device of the user is moving toward the selected location basedon the current location of the client device (step 618). If the serverdevice determines that the client device of the user is moving towardthe selected location based on the current location of the clientdevice, yes output of step 618, then the server device makes adetermination as to whether the client device of the user arrived at theselected location within an estimated time of arrival (step 620). If theserver device determines that the client device of the user did notarrive at the selected location within the estimated time of arrival, nooutput of step 620, then the process returns to step 616 where theserver device monitors the current location of the client device of theuser. If the server device determines that the client device of the userdid arrive at the selected location within the estimated time ofarrival, yes output of step 620, then the server device records movementof the client device of the user at the location using the trackingsystem component (step 622).

In addition, the server device makes a determination as to whether theclient device of the user left the selected location based on dataobtained from the tracking system component (step 624). If the serverdetermines that the client device of the user did not leave the selectedlocation based on the data obtained from the tracking system component,no output of step 624, then the process returns to step 622 where theserver device continues to record the movement of the client device ofthe user at the location. If the server determines that the clientdevice of the user did leave the selected location based on the dataobtained from the tracking system component, yes output of step 624,then the server device makes a determination as to whether anotherlocation exists in the set of locations that the user of the clientdevice wants to go to (step 626).

If the server device determines that another location does exist in theset of locations that the user of the client device wants to go to, yesoutput of step 626, then the process returns to step 606 where theserver device selects another location in the set of locations based onthe data within the profile associated with the user. If the serverdevice determines that another location does not exist in the set oflocations that the user of the client device wants to go to, no outputof step 626, then the process terminates thereafter.

Returning again the step 618, if the server device determines that theclient device of the user is not moving toward the selected locationbased on the current location of the client device, no output of step618, then the server device prompts the user of the client device toselect which location in the set of locations the user is going to (step628). Afterward, the server device makes a determination as to whetherthe user of client device selected a particular location in the set oflocations (step 630). If the server device determines that the user ofclient device did select a particular location in the set of locations,yes output of step 630, then the process returns to step 606 where theserver device selects that particular location in the set of locationsbased on the user's selection. If the server device determines that theuser of client device did not select a particular location in the set oflocations, no output of step 630, then the process terminatesthereafter.

With reference now to FIG. 7A and FIG. 7B, a flowchart illustrating aprocess for detecting a crowd at a site corresponding to a task at alocation is shown in accordance with an illustrative embodiment. Theprocess shown in FIGS. 7A and 7B may be implemented in a server device,such as, for example, server device 302 in FIG. 3. In addition, theserver device may be implemented in a data processing system, such asdata processing system 200 in FIG. 2.

The process begins when the server device detects a presence of a clientdevice of a user at a location in a list of locations the user wants togo to to perform a set of tasks at each location (step 702). The serverdevice may use, for example, a presence detection component, such aspresence detection component 502 at location 500 in FIG. 5, to detectthe presence of the client device of the user at the location. Inaddition, the server device retrieves the set of tasks the user of theclient device wants to perform at the location from a profile associatedwith the user (step 704). The profile associated with the user may be,for example, user profile 320 in FIG. 3.

Subsequent to retrieving the set of tasks the user of the client devicewants to perform at the location in step 704, the server device selectsa task in the set of tasks the user of the client device wants toperform at the location based on data within the profile associated withthe user (step 706). The data in the user profile that the server deviceuses to determine the set of tasks to be performed at the location bythe user may be, for example, preferences, electronic task lists, and/orhistory data associated with the user, such as data in user preferences322, electronic task lists 326, and history data 330 in FIG. 3. Inaddition, the server device monitors a set of data inputs to determine anumber of people currently at a site corresponding to the task (step708). The set of data inputs may be, for example, data inputs 400 inFIG. 4. The site corresponding to the task may be, for example, sitecorresponding to task 508 in FIG. 5.

Further, the server device makes a determination as to whether thenumber of people currently at the site corresponding to the task isgreater than a user-defined threshold level of people for the site (step710). The user-defined threshold level of people for the site may be,for example, a user-defined crowd threshold level in user-defined crowdthreshold levels 328 in FIG. 3. If the server device determines that thenumber of people currently at the site corresponding to the task isgreater than the user-defined threshold level of people for the site,yes output of step 710, then the process proceeds to step 726. If theserver device determines that the number of people currently at the sitecorresponding to the task is not greater than the user-defined thresholdlevel of people for the site, no output of step 610, then the serverdevice maps a route to the site corresponding to the task using amapping system component (step 712). The mapping system component maybe, for example, mapping system component 310 in FIG. 3. Moreover, theserver device may utilize a map of the location, such as store map andinventory data 416 in FIG. 4, to map the route to the site correspondingto the task.

Furthermore, the server device sends the mapped route to the sitecorresponding to the task to the client device of the user (step 714).The server device also monitors a current location of the client deviceof the user using a tracking system component (step 716). The trackingsystem component may be, for example, tracking system component 308 inFIG. 3.

Moreover, the server device makes a determination as to whether theclient device of the user is moving toward the site corresponding to thetask based on the current location of the client device (step 718). Ifthe server device determines that the client device of the user ismoving toward the site corresponding to the task based on the currentlocation of the client device, yes output of step 718, then the serverdevice makes a determination as to whether the client device of the userarrived at the site corresponding to the task within an estimated timeof arrival (step 720). If the server device determines that the clientdevice of the user did not arrive at the site corresponding to the taskwithin the estimated time of arrival, no output of step 720, then theprocess returns to step 716 where the server device monitors the currentlocation of the client device of the user. If the server devicedetermines that the client device of the user did arrive at the sitecorresponding to the task within the estimated time of arrival, yesoutput of step 720, then the server device records activity of the userof the client device at the site corresponding to the task using a videosystem component (step 722). The video system component may be, forexample, video system component 504 in FIG. 5.

In addition, the server device makes a determination as to whether theclient device of the user left the site corresponding to the task (step724). If the server determines that the client device of the user didnot leave the site corresponding to the task based on the data obtainedfrom the tracking system component, no output of step 724, then theprocess returns to step 722 where the server device continues to recordthe activity of the user of the client device at the site correspondingto the task. If the server determines that the client device of the userdid leave the site corresponding to the task based on the data obtainedfrom the tracking system component, yes output of step 724, then theserver device makes a determination as to whether another task exists inthe set of tasks associated with the user of the client device (step726).

If the server device determines that another task does exist in the setof tasks that the user of the client device wants to perform, yes outputof step 726, then the process returns to step 706 where the serverdevice selects another task in the set of tasks based on the data withinthe profile associated with the user. If the server device determinesthat another task does not exist in the set of tasks that the user ofthe client device wants to perform, no output of step 726, then theprocess terminates thereafter.

Returning again the step 718, if the server device determines that theclient device of the user is not moving toward the site corresponding tothe task based on the current location of the client device, no outputof step 718, then the server device prompts the user of the clientdevice to select which task in the set of tasks the user wants toperform (step 728). Afterward, the server device makes a determinationas to whether the user of client device selected a particular task inthe set of tasks (step 730). If the server device determines that theuser of client device did select a particular task in the set of tasks,yes output of step 730, then the process returns to step 706 where theserver device selects that particular task in the set of tasks based onthe user's selection. If the server device determines that the user ofclient device did not select a particular task in the set of tasks, nooutput of step 730, then the process terminates thereafter.

With reference now to FIG. 8A and FIG. 8B, a flowchart illustrating aprocess for a client device is shown in accordance with an illustrativeembodiment. The process shown in FIGS. 8A and 8B may be implemented in aclient device, such as, for example, client device 304 in FIG. 3. Inaddition, the client device may be implemented in a data processingsystem, such as data processing system 200 in FIG. 2.

The process begins when the client device sends a profile associatedwith a user of the client device to a server device (step 802). Theprofile associated with the user may be, for example, user profile 320in FIG. 3. The server device may be, for example, server device 302 inFIG. 3.

Subsequently, the client device makes a determination as to whether theclient device received a mapped route to a location in a set oflocations the user of the client device wants to go to from the serverdevice (step 804). The location may be, for example, location 500 inFIG. 5. If the client device determines that the client device did notreceive a mapped route to a location in a set of locations the user ofthe client device wants to go to from the server device, no output ofstep 804, then the client device sends a request to the server devicefor routing information to a selected location in the set of locationsthe user of the client device wants to go to (step 806) and the processreturns to step 804 thereafter. If the client device determines that theclient device did receive a mapped route to a location in a set oflocations the user of the client device wants to go to from the serverdevice, yes output of step 804, then the client device displays themapped route to the location in the set of locations the user of theclient device wants to go to (step 808). The client device may displaythe mapped route to the location in a display device, such as display214 in FIG. 2.

In addition, the client device makes a determination as to whether theclient device received a prompt from the server device to select alocation in the set of locations the user of the client device wants togo to (step 810). If the client device determines that the client devicedid receive a prompt from the server device to select a location in theset of locations the user of the client device wants to go to, yesoutput of step 810, then the client device sends a selection of aparticular location in the set of locations the user of the clientdevice wants to go to (step 812) and the process returns to step 804thereafter. If the client device determines that the client device didnot receive a prompt from the server device to select a location in theset of locations the user of the client device wants to go to, no outputof step 810, then the client device makes a determination as to whetherthe client device received a mapped route to a site corresponding to atask in a set of tasks the user of the client device wants to perform atthe location from the server device (step 814). The site correspondingto the task may be, for example, site corresponding to task 508 in FIG.5.

If the client device determines that the client device did not receive amapped route to a site corresponding to a task in a set of tasks theuser of the client device wants to perform at the location from theserver device, no output of step 814, then the client device sends arequest to the server device for routing information to a selected taskin the set of tasks the user of the client device wants to perform atthe location (step 816) and the process returns to step 814 thereafter.If the client device determines that the client device did receive amapped route to a site corresponding to a task in a set of tasks theuser of the client device wants to perform at the location from theserver device, yes output of step 814, then the client device displaysthe mapped route to the site corresponding to the task in the set oftasks the user of the client device wants to perform at the location(step 818).

Further, the client device makes a determination as to whether anothertask exists in the set of tasks that the user of the client device wantsto perform at the location (step 820). If the client device determinesthat another task does exist in the set of tasks that the user of theclient device wants to perform at the location, yes output of step 820,then the process returns to step 814. If the client device determinesthat another task does not exist in the set of tasks that the user ofthe client device wants to perform at the location, no output of step820, then the client device makes a determination as to whether anotherlocation exists in the set of locations that the user of the clientdevice wants to go to (step 822). If the client device determines thatanother location does exist in the set of locations that the user of theclient device wants to go to, yes output of step 822, then the processreturns to step 804. If the client device determines that anotherlocation does not exist in the set of locations that the user of theclient device wants to go to, no output of step 822, then the processterminates thereafter.

Thus, illustrative embodiments provide a method, computer system, andcomputer program product for managing movements of a client device userbased on crowd detection using a plurality of data inputs. Thedescriptions of the various illustrative embodiments have been presentedfor purposes of illustration, but are not intended to be exhaustive orlimited to the embodiments disclosed. Many modifications and variationswill be apparent to those of ordinary skill in the art without departingfrom the scope and spirit of the described embodiment. The terminologyused herein was chosen to best explain the principles of the embodiment,the practical application or technical improvement over technologiesfound in the marketplace, or to enable others of ordinary skill in theart to understand the embodiments disclosed here.

The flowchart and block diagrams in the figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousillustrative embodiments. In this regard, each block in the flowchart orblock diagrams may represent a module, segment, or portion of code,which comprises one or more executable instructions for implementing thespecified logical function(s). It should also be noted that, in somealternative implementations, the functions noted in the block may occurout of the order noted in the figures. For example, two blocks shown insuccession may, in fact, be executed substantially concurrently, or theblocks may sometimes be executed in the reverse order, depending uponthe functionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts, or combinations of special purpose hardware andcomputer instructions.

What is claimed is:
 1. A method for detecting crowds, the methodcomprising: selecting, by a computer device, a location in a set oflocations a user of a client device wants to go to based on data withina profile associated with the user; monitoring, by the computer device,a set of data inputs to determine a number of people currently at theselected location; responsive to the computer device determining thatthe number of people currently at the selected location is not greaterthan a user-defined threshold level of people for the selected location,sending, by the computer device, a mapped route to the selected locationto the client device of the user; selecting, by the computer device, atask in a set of tasks the user of the client device wants to perform atthe selected location based on the data within the profile associatedwith the user; monitoring, by the computer device, the set of datainputs to determine a number of people currently at a site within theselected location corresponding to the selected task in the set oftasks; responsive to the computer device determining that the number ofpeople currently at the site within the selected location correspondingto the selected task in the set of tasks is not greater than auser-defined threshold level of people for the site, sending, by thecomputer device, a mapped route to the site within the selected locationcorresponding to the selected task in the set of tasks to the clientdevice of the user; responsive to the computer device determining thatthe client device of the user arrived at the site within the selectedlocation corresponding to the selected task in the set of tasks withinan estimated time of arrival, recording, by the computer device,activity of the user of the client device at the site within theselected location corresponding to the selected task in the set oftasks; and responsive to the computer device determining that the clientdevice of the user left the site within the selected locationcorresponding to the selected task in the set of tasks, determining, bythe computer device, whether another task exists in the set of tasks theuser of the client device wants to perform at the selected location. 2.The method of claim 1 further comprising: detecting, by the computerdevice, a presence of the client device of the user at the selectedlocation; and retrieving, by the computer device, the set of tasks theuser of the client device wants to perform at the selected location fromthe profile associated with the user.
 3. The method of claim 1, whereinthe computer device records the activity of the user of the clientdevice at the site within the selected location corresponding to theselected task using a video camera system.
 4. The method of claim 1further comprising: recording, by the computer device, movement of theclient device of the user at the selected location using a trackingsystem.
 5. The method of claim 1, wherein the computer device estimatesfuture crowd densities at the selected location based on recordedhistorical crowd density patterns at the selected location.
 6. Themethod of claim 1, wherein the computer device monitors a crowd densityat a currently crowded location having greater than the user-definedthreshold level of people on a predetermined time interval basis andreroutes the user of the client device based on the monitored crowddensity.
 7. The method of claim 1, wherein the computer device collectsdata regarding the user of the client device to determine a behaviorpattern of the user at the selected location.
 8. The method of claim 1,wherein the set of data inputs includes at least one of video cameradata, motion sensor data, radio frequency identification reader data,social media web site data, and location map data.
 9. The method ofclaim 1, wherein the computer device receives tracking data from theclient device of the user.
 10. The method of claim 1, wherein the clientdevice of the user is one a cellular telephone, a smart phone, apersonal digital assistant, a gaming device, or a handheld computer.